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  Constraining the Pattern and Magnitude of Projected Extreme Precipitation Change in a Multimodel Ensemble

Kotz, M., Lange, S., Wenz, L., Levermann, A. (2024): Constraining the Pattern and Magnitude of Projected Extreme Precipitation Change in a Multimodel Ensemble. - Journal of Climate, 37, 1, 97-111.
https://doi.org/10.1175/JCLI-D-23-0492.1

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Datensatz-Permalink: https://publications.pik-potsdam.de/pubman/item/item_29133 Versions-Permalink: https://publications.pik-potsdam.de/pubman/item/item_29133_2
Genre: Zeitschriftenartikel

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29133oa.pdf (Verlagsversion), 19MB
 
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 Urheber:
Kotz, Maximilian1, Autor              
Lange, Stefan1, Autor              
Wenz, Leonie1, Autor              
Levermann, Anders1, Autor              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: Projections of precipitation extremes over land are crucial for socioeconomic risk assessments, yet model discrepancies limit their application. Here we use a pattern-filtering technique to identify low-frequency changes in individual members of a multimodel ensemble to assess discrepancies across models in the projected pattern and magnitude of change. Specifically, we apply low-frequency component analysis (LFCA) to the intensity and frequency of daily precipitation extremes over land in 21 CMIP-6 models. LFCA brings modest but statistically significant improvements in the agreement between models in the spatial pattern of projected change, particularly in scenarios with weak greenhouse forcing. Moreover, we show that LFCA facilitates a robust identification of the rates at which increasing precipitation extremes scale with global temperature change within individual ensemble members. While these rates approximately match expectations from the Clausius-Clapeyron relation on average across models, individual models exhibit considerable and significant differences. Monte Carlo simulations indicate that these differences contribute to uncertainty in the magnitude of projected change at least as much as differences in the climate sensitivity. Last, we compare these scaling rates with those identified from observational products, demonstrating that virtually all climate models significantly underestimate the rates at which increases in precipitation extremes have scaled with global temperatures historically. Constraining projections with observations therefore amplifies the projected intensification of precipitation extremes as well as reducing the relative error of their distribution.

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Sprache(n): eng - Englisch
 Datum: 2023-10-022023-12-112024-01-01
 Publikationsstatus: Final veröffentlicht
 Seiten: 15
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: Organisational keyword: RD4 - Complexity Science
Organisational keyword: RD3 - Transformation Pathways
PIKDOMAIN: RD4 - Complexity Science
PIKDOMAIN: RD3 - Transformation Pathways
Research topic keyword: Atmosphere
Research topic keyword: Extremes
Research topic keyword: Weather
Regional keyword: Global
Model / method: Nonlinear Data Analysis
DOI: 10.1175/JCLI-D-23-0492.1
Working Group: Data-based analysis of climate decisions
Working Group: Data-Centric Modeling of Cross-Sectoral Impacts
MDB-ID: pending
 Art des Abschluß: -

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Projektinformation

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Projektname : Impact of intensified weather extremes on Europe's economy (ImpactEE)
Grant ID : 93350
Förderprogramm : Europe and Global Challenges
Förderorganisation : VolkswagenStiftung
Projektname : Provision of climate and bio-physical forcing data for health impact projections
Grant ID : 409670289
Förderprogramm : FOR 2936: Climate Change and Health in Sub-Saharan Africa
Förderorganisation : Deutsche Forschungsgemeinschaft (DFG)
Projektname : Quantifying direct and indirect costs of climate-related hazards (QUIDIC)
Grant ID : 01LP1907A
Förderprogramm : Ökonomie des Klimawandels
Förderorganisation : BMBF
Projektname : RECEIPT
Grant ID : 820712
Förderprogramm : Horizon 2020 (Horizon 2020) (H2020-LC-CLA-2018-2)
Förderorganisation : European Commission (EC)

Quelle 1

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Titel: Journal of Climate
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 37 (1) Artikelnummer: - Start- / Endseite: 97 - 111 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals254
Publisher: American Meteorological Society (AMS)